采用卡尔曼滤波算法的MEMS器件姿态测量  

Attitude Measurement of MEMS Devices by Using the Kalman Filter Algorithm

作　　者：周树道[1] 金永奇[1] 卫克晶[1] 刘星[1] 

机构地区：[1]解放军理工大学气象海洋学院,江苏南京211101

出　　处：《实验室研究与探索》2015年第2期38-42,共5页Research and Exploration In Laboratory

摘　　要：针对小型无人机上使用的MEMS惯性传感器在精度、噪声上存在的问题,采用卡尔曼滤波算法结合角度传感器、加速度传感器、磁阻传感器的传感信息,来解算姿态角最优值。采用四元素法确立了捷联矩阵,利用三轴陀螺仪传感器所得到的角速度信息建立系统状态方程,利用三轴加速度传感器和磁阻传感器信息建立了系统测量方程,进而设计了一种卡尔曼滤波器来滤除MEMS传感器存在的随机噪声,并解算出了小型无人机的姿态角。通过实验室静态测试和动态测试表明,无人机姿态角解算结果与实际值对比,误差能够控制在2°以内,可满足工程应用要求。For the problems of MEMS inertial sensors in accuracy and noise, Kalman filter algorithm is presented by fusing multi-sensor information obtained from angle sensor, acceleration sensor and magnetoresistive sensor to get optimal result of attitude angle. At first, a strapdown equation described by quaternion is established ; an equation of state of the system is established by using tri-axis gyroscopes data, and a system measurement equation is established by using tri- axis aecelerometer and MARG sensor data. Then a Kalman filter is designed to remove the random noise of the MEMS sensors and calculated attitude angles. Static test and dynamic test show that the error of attitude solver results can be controlled within 2°, and the design satisfies engineering requirement.

关 键 词：卡尔曼滤波 姿态角解算 微机电系统传感器 四元素法 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置]